Phosphodiesterase 4 Inhibitor Cilomilast Inhibits Fibroblast-Mediated Collagen Gel Degradation Induced by Tumor Necrosis Factor- <b>α</b> and Neutrophil Elastase
Bibliographic record
Abstract
Tissue destruction, resulting in emphysema, can be a consequence of several pathologic processes. The current study evaluated the effects of the phosphodiesterase (PDE)4 inhibitor, cilomilast, and other PDE inhibitors on the ability of fibroblasts to degrade extracellular matrix. Using the three-dimensional collagen gel culture system, fibroblasts (HFL-1) were cultured with tumor necrosis factor (TNF)-alpha, known to induce matrix metalloproteinase (MMP) release, and/or neutrophil elastase (NE), which can induce MMP activation. On Day 4, gels containing TNF-alpha and NE were significantly degraded (20.8 +/- 2.9% of original collagen content). Cilomilast (10 micro M) inhibited this degradation (84.4 +/- 8.4%). Amrinone, a PDE3 inhibitor, and zaprinast, a PDE5 inhibitor, had no effect. Gelatin zymography and immunoblotting revealed that fibroblasts cultured with TNF-alpha released increased amounts of latent MMP-1 and -9. The addition of NE resulted in the conversion of MMP-1 and -9 to their active forms, indicative of collagen degradation. Cilomilast inhibited the release of MMP-1 and -9, as well as conversion of MMP-1 to its active form. Using real-time PCR analysis, cilomilast's effect on MMP-1 release was not associated with the proteinase's mRNA expression, suggesting that the inhibition of release is regulated at the post-transcriptional level. These results suggest that cilomilast may be a potentially effective therapeutic agent in diseases characterized by excessive tissue destruction, such as emphysema.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".